Data Science in Finance and Economics最新文献_第5页

Analysis of chaotic economic models through Koopman operators, EDMD, Takens' theorem and Machine Learning 利用Koopman算子、EDMD、Takens定理和机器学习分析混沌经济模型

Data Science in Finance and Economics Pub Date : 1900-01-01 DOI: 10.3934/dsfe.2022021

J. Leventides, E. Melas, C. Poulios, P. Boufounou

引用次数: 1

Volatility spillovers among MIST stock markets 新兴市场股票市场的波动溢出效应

Data Science in Finance and Economics Pub Date : 1900-01-01 DOI: 10.3934/dsfe.2022004

Deniz Sevinc

{"title":"Volatility spillovers among MIST stock markets","authors":"Deniz Sevinc","doi":"10.3934/dsfe.2022004","DOIUrl":"https://doi.org/10.3934/dsfe.2022004","url":null,"abstract":"\u0000 This paper examines the effects of volatility spillover between MIST stock markets. We used daily data from January 3, 2012, to November 16, 2021, and the test of causality in variance, including structural breaks. First, we observed no structural break for Turkey and Indonesia, but there is a structural break in each South Korean and Mexican stock markets. A structural break is found for Mexico the day, aka \"El Betito\" was arrested. Likewise, we detected a structural break on the first day of the Covid-19 case for South Korea. We surprisingly observed that Covid-19 did not cause a structural break in these markets during the period analyzed, except in South Korea. GARCH (1, 1) models, including structural breaks, show that all series are temporarily and permanently affected by their own shocks. The causality in variance test reveals that MIST countries have volatility spillover effects on each other. There is bidirectional causality in variance between all markets, except South Korea and Mexico. The Mexican stock market is a volatility transmitter for South Korea, but vice versa. The paper indicates a connection in terms of the financial markets of MIST countries, and they are affected by each other's shocks, according to the study results.\u0000","PeriodicalId":290300,"journal":{"name":"Data Science in Finance and Economics","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127861549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Optimization proposals to the payment clearing 支付清算优化建议

Data Science in Finance and Economics Pub Date : 1900-01-01 DOI: 10.3934/dsfe.2023005

Roylan Martinez

引用次数: 1

Revisiting the Energy-Growth nexus with debt channel. A wavelet time-frequency analysis for a panel of Eurozone-OECD countries 重新审视能源增长与债务渠道的关系。一组欧元区-经合组织国家的小波时频分析

Data Science in Finance and Economics Pub Date : 1900-01-01 DOI: 10.3934/dsfe.2023008

Mohamed Awada, Roman Mestre

引用次数: 1

Measuring the effects of investor attention on China's stock returns 衡量投资者关注对中国股市回报的影响

Data Science in Finance and Economics Pub Date : 1900-01-01 DOI: 10.3934/dsfe.2021018

Yi Chen, Zhehao Huang

{"title":"Measuring the effects of investor attention on China's stock returns","authors":"Yi Chen, Zhehao Huang","doi":"10.3934/dsfe.2021018","DOIUrl":"https://doi.org/10.3934/dsfe.2021018","url":null,"abstract":"\u0000 The increasing abundance of information leads to the scarcity of investor attention, which has become an important factor affecting the financial market. Search engines play the role of information retrieval and record the search behavior of investors, which is a direct and accurate measure of investor attention. This paper investigates the relationship between investor attention and China's stock market. Considering the relationship with stock returns as the mainline, we take the Baidu index as a substitute variable of investor attention to deeply study the correlation and the time-varying nature between investor attention and China's stock returns. To this end, we used quantile regression to examine the relationship over the period 2006–2021 to capture its evolution during calm and turbulent times. We thus investigated the effect of investor attention on the mean and other quantiles. Our findings show that the relationship between investor attention and China's stock returns exhibits time-variation as investor attention significantly impacts the dynamics of China's stock returns, but its sign and effect vary per quantile: investor attention is negatively correlated with stock returns at low quantiles, but it turns positive at high quantiles. In addition, to test the model's robustness, variable replacement method and model replacement method are used to conduct significance tests, respectively. The results are equally significant.\u0000","PeriodicalId":290300,"journal":{"name":"Data Science in Finance and Economics","volume":"2 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131437046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Autonomous human-machine teams: Reality constrains logic, but hides the complexity of data dependency 自主的人机团队:现实限制了逻辑，但隐藏了数据依赖的复杂性

Data Science in Finance and Economics Pub Date : 1900-01-01 DOI: 10.3934/dsfe.2022023

W. Lawless

{"title":"Autonomous human-machine teams: Reality constrains logic, but hides the complexity of data dependency","authors":"W. Lawless","doi":"10.3934/dsfe.2022023","DOIUrl":"https://doi.org/10.3934/dsfe.2022023","url":null,"abstract":"\u0000 In this review, scientists have struggled to apply logic to rational beliefs of collectives, concluding that belief logics fail in the face of conflict and uncertainty where reality governs. We have generalized this finding by concluding that traditional social science based on independent concepts about individuals and interpretations of reality requires too many fixes to address its replication crisis, yet ignores the generalization of individuals to teams, for which social science has become largely irrelevant. Unable to process the data dependencies of autonomous human-machine teammates in orthogonal roles for successful teams, producing zero correlations, this problem extends to traditional social science predicated on the belief that perceptions in closed systems (laboratories) are eality. But, as the National Academy of Sciences has noted, this assumption fails in open spaces. Thus, the study of group processes has de-evolved to become overly focused on individuals (e.g., biases), which do not generalize to teams. For a theory of autonomous human-machine teams and systems, generalization is critical. By using an open-systems approach, we have been able to explain the failures of social science, and its ack of success in the field, and we have generalized to autonomous human-machine teams and human-human teams. We extend our theory to conclude that traditional belief logics uses assumptions that, if not tested in reality (e.g., with debates), can be lethal (e.g, DoD's drone tragedy in Afghanistan in 2021). We conclude that an AI machine operating interdependently with a human teammate, jointly challenging each other's beliefs about reality while sharing and shaping their experiences, is the path to autonomy in the open, justifying our research program.\u0000","PeriodicalId":290300,"journal":{"name":"Data Science in Finance and Economics","volume":"226 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122649855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Retrospective technology of segmentation and classification for GARCH models based on the concept of the $ epsilon $-complexity of continuous functions 基于连续函数复杂度概念的GARCH模型回溯式分割分类技术

Data Science in Finance and Economics Pub Date : 1900-01-01 DOI: 10.3934/dsfe.2022012

A. Piryatinska, B. Darkhovsky

引用次数: 0

Customers' adoption of financial services offered by banks and fintechs partnerships: evidence of a transitional economy 客户采用银行提供的金融服务和金融科技合作伙伴关系:经济转型的证据

Data Science in Finance and Economics Pub Date : 1900-01-01 DOI: 10.3934/dsfe.2021005

Y. H. Hoang, D. Nguyen, L. Tran, N. Nguyen, N. B. Vu

{"title":"Customers' adoption of financial services offered by banks and fintechs partnerships: evidence of a transitional economy","authors":"Y. H. Hoang, D. Nguyen, L. Tran, N. Nguyen, N. B. Vu","doi":"10.3934/dsfe.2021005","DOIUrl":"https://doi.org/10.3934/dsfe.2021005","url":null,"abstract":"In recent years, the number of fintech startups has increased substantially, especially those that offer financial services in areas considered as traditional advantage of commercial banks such as payment, deposit or lending services. This paper examines the cooperation in the provision of financial services between banks and Fintech from consumers’ perspective, which is the customers’ adoption of financial services offered by the partnership between banks and Fintechs. The study employs SEM utilizing data of 234 customers using financial services in Vietnam to identify the factors influence their behaviors and intention to use financial services offered by banks and fintechs partnerships. The findings indicate that perceived usefulness, brand image, user innovativeness and trust have positive effects on customers’ attitude and consequently on their intention to use. However, there is no evidence regarding the impact of perceived ease of use and perceived risks on behavior and intention to use of customers. The findings also provide more evidence on the factors that influence the intention of customers’ technology acceptance in the traditional Technology Acceptance Model (TAM).","PeriodicalId":290300,"journal":{"name":"Data Science in Finance and Economics","volume":"211 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121222469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Dynamics of stability of the world economic system 世界经济体系稳定的动力

Data Science in Finance and Economics Pub Date : 1900-01-01 DOI: 10.3934/dsfe.2023006

Anatoly Kilyachkov, L. Chaldaeva, Nikolai A. Kilyachkov

{"title":"Dynamics of stability of the world economic system","authors":"Anatoly Kilyachkov, L. Chaldaeva, Nikolai A. Kilyachkov","doi":"10.3934/dsfe.2023006","DOIUrl":"https://doi.org/10.3934/dsfe.2023006","url":null,"abstract":"\u0000\u0000The current global economic crisis has actualized the problem of studying non-equilibrium processes in the economy. To approach the problem, a discrete dynamic model (DDM) was developed that describes the dynamics of the rate of change in the global GDP for the period 1961-2021. This paper publishes the results of studies of two types of stability. The first is connected with the global economic system stability, which can be described by a DDM in different time periods. The second studies sensitivity of the DDM to the annual GDP growth values that were used to construct it (sensitivity analysis). The conducted research depicted the various periods of development of the global economic system, characterized by varying degrees of stability. The DDM determined that during periods of crises, the stability of the global economic system decreases. Our studies have shown that at present the world economic system is on the verge of a complete loss of stability. To assess the sensitivity of the DDM to the input data, a sensitivity indicator was introduced. It was found that the DDM is insensitive to input data during periods of crisis, i.e., the results obtained are reliable. In turn, periods of stable development of the global economic system are characterized by less reliability in the DDM results.\u0000\u0000","PeriodicalId":290300,"journal":{"name":"Data Science in Finance and Economics","volume":"190 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116530880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analysis and prediction of American economy under different government policy based on stepwise regression and support vector machine modelling 基于逐步回归和支持向量机建模的不同政府政策下美国经济分析与预测

Data Science in Finance and Economics Pub Date : 1900-01-01 DOI: 10.3934/dsfe.2023001

Yongqi Lin, Xuejie Chen, H. Lan

引用次数: 0